Patient motion is an ever-present potential cause of artifacts that can limit the accuracy of diagnostic imaging. The problem is especially significant for imaging modalities such as SPECT and PET, which require the patient to remain motionless for protracted periods of time. Compensation strategies for motion that rely exclusively on the emission data itself, although commercially available, are inadequate for robust clinical usage. The goal of the proposed investigations is to determine if information from a visual-tracking-system will provide a robust compensation for patient motion as part of iterative reconstruction. By visual-trackingsystem it is meant a computational system that processes stereo-images taken by optical cameras thereby providing a source of motion information that is independent of the SPECT system. Motion of the chest and abdomen will be determined by tracking the locations of a pattern that is part of a stretchy garment wrapped about these portions of the patient. The types of patient motion for which compensation will be investigated with the visual-tracking-system are rigid-body motion, non-rigid-body motion, respiratory motion, upward-creep of the heart, and motion between sequential emission and transmission, CT or MRI imaging. The ultimate test of the success of the visual-tracking-system based compensation will be physician-observer ROC studies comparing the detection accuracy of coronary artery disease with and without motion compensation for patients undergoing SPECT perfusion imaging. The first specific aim is to perfect the visual-tracking-system and determine its accuracy for tracking rigid-body motion. The second specific aim is to modify the visual-tracking-system to include compensation for respiratory motion, and upward-creep of the heart. The third specific aim is to investigate the need for non-rigid-body motion, and whether the motion of the locations in the pattern on the garment can predict the internal motion of structures when coupled with knowledge of the individual patient's anatomy from multi-modality imaging on the same imaging bed. The fourth specific aim is to develop a motion-compensation algorithm that employs the information from the visual-tracking-system to compensate for the above motions as part of list-mode iterative reconstruction. The fifth specific aim is to determine whether the visual-tracking-system and motioncompensation algorithm are able to improve the diagnostic accuracy of cardiac-perfusion SPECT imaging as determined by human-observer ROC studies with clinical images.